Location sensing of slowly moving objects in an indoor environment has created a growing interest in location-aware services and applications in various market segments. In the retail industry, for example, shopping carts equipped with a personal shopping assistant enriched with some additional location positioning functionality can guide customers through a store, provide them with location-based product information, and alert them to promotions and discounts as they walk through the aisles. However, customer satisfaction, and thereby the success of this advanced shopping service, depends on the achievable position accuracy.
Location tracking of mobile objects in an indoor environment can be performed with various techniques, based on mechanical, acoustical, ultra-sonic, optical, infrared, inertial, or radio-signal measurements. Among these systems, radio-based location positioning systems are most frequently used to sense and track the position of moving objects in an indoor environment. A radio receiver attached to the objects measures the signal strength, the angle of arrival, or the arrival-time difference of received radio signals that are transmitted by multiple pre-installed reference transponder units. Since the locations of the radio transponders are known, a triangulation or signature method can be applied to determine the physical location of the moving object. As far as the radio technology is concerned, the wireless personal-area and network technology as specified by the IEEE 802.15.x standardization body and the ZigBee Alliance, of San Ramon, Calif., USA, are well-suited for obtaining low-cost implementations. However, wireless local area network (WLAN) technology can also be very attractive in buildings where an infrastructure is already deployed.
The location position estimates obtained from radio signal strength measurements in a location positioning system using single-antenna radio transceivers are reliable and stable in the long term, but suffer from a large error variance due to the fading radio channel. According to theory, a good signal strength estimate can be computed in the radio receiver by averaging N signal strength samples taken every Ts seconds. Upon application of the strong law of large numbers, this sample mean converges to the statistical average of the received signal power with probability 1 as N→∞, if the input signal are uncorrelated, the noise is white, and the channel correlation vanishes with increasing time lag. In a typical indoor environment, however, the wireless channel changes very slowly, i.e. the channel coherence time is large. Consequently, subsequent channel gains are highly correlated and averaging has to be performed over a large number, N, of samples to yield an estimate very close to the real signal strength value. Therefore, position estimates derived from signal strength measurements with a single-antenna receiver can only be updated rather infrequently and are not well-suited for tracking the location position of a moving object.